Enterprise AI in the Cloud : A Practical Guide to Deploying End-To-End Machine Learning and ChatGPT Solutions.

Format:

Book

Author/Creator:

Jay, Rabi.

Series:

Tech Today Series

Language:

English

Subjects (All):

Artificial intelligence--Computer programs.

Artificial intelligence.

Technology.

Physical Description:

1 online resource (527 pages)

Edition:

1st ed.

Place of Publication:

Newark : John Wiley & Sons, Incorporated, 2024.

Summary:

"Embrace emerging AI trends and integrate your operations with cutting-edge solutions Enterprise AI in the A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises. You'll also discover best practices on optimizing cloud infrastructure for scalability and automation. Enterprise AI in the Cloud helps you gain a solid understanding. Whether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise." -- Goodreads.

Contents:

Cover

Title Page

Copyright Page

Acknowledgments

About the Author

About the Technical Editor

Contents

Introduction

How This Book Is Organized

Who Should Read This Book?

Data Scientists and AI Teams

IT Leaders and Teams

Students and Academia

Consultants and Advisors

Business Strategists and Leaders

C-Level Executives

Why You Should Read This Book

Unique Features

Comprehensive Coverage of All Aspects of Enterprise-wide AI Transformation

Case Study Approach

Coverage of All Major Cloud Platforms

Discussion of Nontechnical Aspects of AI

Best Practices for MLOps and AI Governance

Up-to-Date Content

Hands-on Approach

Part I Introduction

Chapter 1 Enterprise Transformation with AI in the Cloud

Understanding Enterprise AI Transformation

Why Some Companies Succeed at Implementing AI and ML While Others Fail

Transform Your Company by Integrating AI, ML and Gen AI into Your Business Processes

Adopt AI-First to Become World-Class

Importance of an AI-First Strategy

Prioritize AI and Data Initiatives

Leveraging Enterprise AI Opportunities

Enable One-to-One, Personalized, Real-Time Service for Customers at Scale

Enterprise-wide AI Opportunities

Growing Industry Adoption of AI

Workbook Template - Enterprise AI Transformation Checklist

Summary

Review Questions

Answer Key

Chapter 2 Case Studies of Enterprise AI in the Cloud

Case Study 1: The U.S. Government and the Power of Humans and Machines Working Together to Solve Problems at Scale

Revolutionizing Operations Management with AI/ML

Enabling Solutions for Improved Operations

Case Study 2: Capital One and How It Became a Leading Technology Organization in a Highly Regulated Environment

Building Amazing Experiences Due to Data Consolidation.

Becoming Agile and Scalable by Moving Data Centers Into the Cloud

Building a Resilient System by Embracing Cloud-Native Principles

Impact of Cloud-First Thinking on DevOps, Agile Development, and Machine Learning

Becoming an AI-First Company: From Cloud Adoption to Thrilling Customer Experiences

Case Study 3: Netflix and the Path Companies Take to Become World-Class

Cloud and AI Technology: A Game-Changer for Netflix's Business Model and Success

Cloud Infrastructure and AI Adoption Drives Process Transformation

Process Transformation Drives Organizational Change

Workbook Template - AI Case Study

Part II Strategizing and Assessing for AI

Chapter 3 Addressing the Challenges with Enterprise AI

Challenges Faced by Companies Implementing Enterprise-wide AI

Business-Related Challenges

Data- and Model-Related Challenges

Platform-Related Challenges

How Digital Natives Tackle AI Adoption

They Are Willing to Take Risks

They Have an Advantage in Data Collection and Curation Capabilities

They Attract Top Talent Through Competitive Compensation and Perks

Get Ready: AI Transformation Is More Challenging Than Digital Transformation

Complexities of Skill Sets, Technology, and Infrastructure Integration

The Importance of Data Infrastructure and Governance

Change Management to Redefine Work Processes and Employee Mindsets

Regulatory Concerns: Addressing Bias, Ethical, Privacy, and Accountability Risks

Choosing Between Smaller PoC Point Solutions and Large-Scale AI Initiatives

The Challenges of Implementing a Large-Scale AI Initiative

Navigate the Moving Parts, Stakeholders, and Technical Infrastructure

Resource Allocation Challenges in Large-Scale AI Initiatives

Overcome Resistance to Change.

Data Security, Privacy, Ethics, Compliance, and Reputation

Build a Business Case for Large-Scale AI Initiatives

Factors to Consider

Workbook Template: AI Challenges Assessment

Chapter 4 Designing AI Systems Responsibly

The Pillars of Responsible AI

Robust AI

Collaborative AI

Trustworthy AI

Scalable AI

Human-centric AI

Workbook Template: Responsible AI Design Template

Chapter 5 Envisioning and Aligning Your AI Strategy

Step-by-Step Methodology for Enterprise-wide AI

The Envision Phase

The Align Phase

Workbook Template: Vision Alignment Worksheet

Chapter 6 Developing an AI Strategy and Portfolio

Leveraging Your Organizational Capabilities for Competitive Advantage

Focus Areas to Build Your Competitive Advantage

Driving Competitive Advantage Through AI

Initiating Your Strategy and Plan to Kickstart Enterprise AI

Manage Your AI Strategy, Portfolio, Innovation, Product Lifecycle, and Partnerships

Define Your AI Strategy to Achieve Business Outcomes

Prioritize Your Portfolio

Strategy and Execution Across Phases

Workbook Template: Business Case and AI Strategy

Chapter 7 Managing Strategic Change

Accelerating Your AI Adoption with Strategic Change Management

Phase 1: Develop an AI Acceleration Charter and Governance Mechanisms for Your AI Initiative

Phase 2: Ensure Leadership Alignment

Phase 3: Create a Change Acceleration Strategy

Workbook Template: Strategic Change Management Plan

Part III Planning and Launching a Pilot Project

Chapter 8 Identifying Use Cases for Your AI/ML Project

The Use Case Identification Process Flow.

Educate Everyone as to How AI/ML Can Solve Business Problems

Define Your Business Objectives

Identify the Pain Points

Start with Root-Cause Analysis

Identify the Success Metrics

Explore the Latest Industry Trends

Review AI Applications in Various Industries

Map the Use Case to the Business Problem

Prioritizing Your Use Cases

Define the Impact Criteria

Define the Feasibility Criteria

Assess the Impact

Assess the Feasibility

Prioritize the Use Cases

Review and Refine the Criteria

Choose the Right Model

Use Cases to Choose From

AI Use Cases for DevOps

AI for Healthcare and Life Sciences

AI Enabled Contact Center Use Cases

Business Metrics Analysis

Content Moderation

AI for Financial Services

Cybersecurity

Digital Twinning

Identity Verification

Intelligent Document Processing

Intelligent Search

Machine Translation

Media Intelligence

ML Modernization

ML-Powered Personalization

Computer Vision

Personal Protective Equipment

Generative AI

Workbook Template: Use Case Identification Sheet

Chapter 9 Evaluating AI/ML Platforms and Services

Benefits and Factors to Consider When Choosing an AI/ML Service

Benefits of Using Cloud AI/ML Services

Factors to Consider When Choosing an AI/ML Service

AWS AI and ML Services

AI Services

Amazon SageMaker

AI Frameworks

Differences Between Machine Learning Algorithms, Models, and Services

Core AI Services

Text and Document Services

Chatbots: Amazon Lex

Speech

Vision Services

Specialized AI Services

Business Processing Services

Kendra for Search

Code and DevOps

Industrial Solutions

Healthcare Solutions

Machine Learning Services

Amazon SageMaker Canvas

SageMaker Studio Lab.

The Google AI/ML Services Stack

For Data Scientists

For Developers

The Microsoft AI/ ML Services Stack

Azure Applied AI Services

Azure Cognitive Services

Azure Machine Learning

Other Enterprise Cloud AI Platforms

Dataiku

DataRobot

KNIME

IBM Watson

Salesforce Einstein AI

Oracle Cloud AI

Workbook Template: AI/ML Platform Evaluation Sheet

Chapter 10 Launching Your Pilot Project

Launching Your Pilot

Planning for Launch

Recap of the Envision Phase

Planning for the Machine Learning Project

Following the Machine Learning Lifecycle

Business Goal Identification

Machine Learning Problem Framing

Data Processing

Model Development

Model Deployment

Model Monitoring

Workbook Template: AI/ML Pilot Launch Checklist

Part IV Building and Governing Your Team

Chapter 11 Empowering Your People Through Org Change Management

Succeeding Through a People-centric Approach

Evolve Your Culture for AI Adoption, Innovation, and Change

Redesign Your Organization for Agility and Innovation with AI

Aligning Your Organization Around AI Adoption to Achieve Business Outcomes

Workbook Template: Org Change Management Plan

Note

Chapter 12 Building Your Team

Understanding the Roles and Responsibilities in an ML Project

Build a Cross-Functional Team for AI Transformation

Adopt Cloud and AI to Transform Current Roles

Customize Roles to Suit Your Business Goals and Needs

Workbook Template: Team Building Matrix

Part V Setting Up Infrastructure and Managing Operations

Chapter 13 Setting Up an Enterprise AI Cloud Platform Infrastructure

Reference Architecture Patterns for Typical Use Cases.

Customer 360-Degree Architecture.

Notes:

Includes index.

Description based on publisher supplied metadata and other sources.

Other Format:

Print version: Jay, Rabi Enterprise AI in the Cloud

ISBN:

9781394213061

1394213069

9781394213078

1394213077

OCLC:

1415869931